There are many studies that deal with the performance of methods of efficiency measurement. Most of them use Monte Carlo simulations. However, these studies have exclusively considered technologies modelled by output-oriented translog production functions (such as Cobb-Douglas functions in particular), which allow factor substitution. Moreover, only two studies analyse Stochastic Non-smooth Envelopment of Data (StoNED) – a new method, which combines elements of Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA) – for multi-output technologies. This paper presents complementary results from a series of Monte Carlo simulations with examples of two-input, two-output technologies that are modelled by Leontief functions or are characterised by rigidly coupled products. Contrary to previous results, in our analyses DEA generates competitive or even the best results in scenarios with few noise. Furthermore, StoNED equals the performance of SFA, provided that both methods are adapted to the orientation of the underlying technology.